Abstract
Hand vein recognition systems are more robust against external influences which degrade the image quality like dust or dirt on the sensor or skin surface conditions than fingerprint ones. We investigate the robustness of several hand vein feature extraction and matching schemes against different types of image distortions, related to conditions occurring during the acquisition of hand vein images. These distortions correspond to sensor defects, bad system design and problems in the use of the sensor. The impact on the recognition accuracy is quantified in terms of the EER and compared across the different schemes and different types of distortions.
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